Entropy-based optimum test points selection for analog fault dictionary techniques
Entropy-based optimum test points selection for analog fault dictionary techniques
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DOI：
10.1109/tim.2004.827085
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发表时间：
2004-05
影响因子：
5.6
通讯作者：
J. Starzyk;Dong Liu;Zhi-Hong Liu;D. E. Nelson;J. Rutkowski
中科院分区：
文献类型：
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作者：
J. Starzyk;Dong Liu;Zhi-Hong Liu;D. E. Nelson;J. Rutkowski
针对模拟故障诊断中的词典技术，提出了一种选择最优测试点集的有效方法。这是通过基于可用的测试点搜索熵指数的最小值来完成的。首先，构造二维整数编码字典，字典的条目是与故障和测试点相关的测量值。因此，选择最优测试点的问题被转换为选择隔离字典行的列。然后，使用测试点的最小熵指数评估根据其模糊集的大小选择列的可能性。最后，选取熵指数最小的测试点构建最优测试点集。提出的基于熵的局部最小测试点选择方法在计算代价上是多项式有界的。通过统计实验，将本文提出的方法与其他已报道的测点选取方法进行了比较。结果表明，该方法能更有效、更准确地找到局部最优测试点集，适用于大规模模拟系统。
An efficient method to select an optimum set of test points for dictionary techniques in analog fault diagnosis is proposed. This is done by searching for the minimum of the entropy index based on the available test points. First, the two-dimensional integer-coded dictionary is constructed whose entries are measurements associated with faults and test points. The problem of optimum test points selection is, thus, transformed to the selection of the columns that isolate the rows of the dictionary. Then, the likelihood for a column to be chosen based on the size of its ambiguity set is evaluated using the minimum entropy index of test points. Finally, the test point with the minimum entropy index is selected to construct the optimum set of test points. The proposed entropy-based method to select a local minimum set of test points is polynomial bounded in computational cost. The comparison between the proposed method and other reported test points selection methods is carried out by statistical experiments. The results indicate that the proposed method more efficiently and more accurately finds the locally optimum set of test points and is practical for large scale analog systems.